World News from data (good & bad)
Significant changes vs. 10 days ago in transmission rates, ICU demand, and cases & deaths data.
- Transmission rate:
- ICU need
- โญ Bad news: higher ICU need ๐ซ๐ท ๐ช๐ธ ๐ฆ๐ท ๐ฎ๐น ๐ฌ๐พ ๐ฒ๐ฉ ๐ต๐พ ๐ญ๐ท
- ๐ข Good news: lower ICU need ๐ฐ๐ฌ ๐ธ๐ช ๐ต๐ฆ ๐บ๐ธ ๐ฟ๐ฆ ๐ง๐ท ๐ง๐ช ๐ง๐ด ๐ฒ๐ฝ ๐ฉ๐ด ๐ธ๐ป ๐ฆ๐ฒ ๐ฒ๐ช ๐จ๐ฑ ๐ฌ๐ฒ ๐ฒ๐ฐ ๐ฑ๐บ ๐ง๐ธ ๐ท๐ธ ๐ฐ๐ฟ ๐ช๐จ ๐ด๐ฒ
- New cases and deaths:
- โญ Bad news: new first significant outbreaks ๐น๐น
- ๐ข Good news: no new cases or deaths
- Mixed news: no new deaths, only new cases ๐ง๐ซ ๐น๐ฌ ๐ฑ๐ท ๐ฑ๐บ ๐ธ๐ฌ ๐ฌ๐ฆ ๐จ๐ซ ๐ธ๐ธ ๐ฒ๐พ ๐จ๐พ ๐ณ๐ฟ ๐น๐ญ ๐ณ๐ช ๐ฌ๐ถ
- No news: continously inactive countries ๐น๐ฟ
- Deaths burden:
- Appendix:
Transmission rate:
Large increase in transmission rate vs. 10 days ago, that might mean a relapse, new wave, worsening outbreak.
- Countries are sorted by size of change in transmission rate.
- Includes only countries that were previously active (more than 100 estimated new cases).
- "Large increase" = at least +2% change.
Large decrease in transmission rate vs. 10 days ago, that might mean a slowing down / effective control measures.
- Countries are sorted by size of change in transmission rate.
- Includes only countries that were previously active (more than 100 estimated new cases).
- "Large decrease" = at least -2% change.
Large increases in need for ICU beds per 100k population vs. 10 days ago.
- Only countries for which the ICU need increased by more than 0.2 (per 100k).
Large decreases in need for ICU beds per 100k population vs. 10 days ago.
- Only countries for which the ICU need decreased by more than 0.1 (per 100k).
Countries that have started their first significant outbreak (crossed 1000 total reported cases or 20 deaths) vs. 10 days ago.
New countries with no new cases or deaths vs. 10 days ago.
- Only considering countries that had at least 1000 estimated total cases and at least 10 total deaths and had an active outbreak previously.
New countries with no new deaths (only new cases) vs. 10 days ago.
- Only considering countries that had at least 1000 estimated total cases and at least 10 total deaths and had an active outbreak previously.
Countries that had no new cases or deaths 10 days ago or now.
- Only considering countries that had at least 1000 estimated total cases and at least 10 total deaths.
- Caveat:these countries may have stopped reporting data like Tanzania.
Countries with significantly higher recent death burden per 100k population vs. 10 days ago.
- "Significantly higher" = 100% more.
- Only considering countries that had at least 10 recent deaths in both timeframes, and death burden of at least 0.1 per 100k.
Countries with significantly lower recent death burden per 100k population vs. 10 days ago.
- "Significantly lower" = 50% less
- Only considering countries that had at least 10 recent deaths in both timeframes, and death burden of at least 0.1 per 100k.
Methodology
- I'm not an epidemiologist. This is an attempt to understand what's happening, and what the future looks like if current trends remain unchanged.
- Everything is approximated and depends heavily on underlying assumptions.
- Transmission rate calculation:
- Growth rate is calculated over the 5 past days by averaging the daily growth rates.
- Confidence bounds are calculated from the weighted standard deviation of the growth rate over the last 5 days. Model predictions are calculated for growth rates within 1 STD of the weighted mean. The maximum and minimum values for each day are used as confidence bands. Countries with highly noisy transmission rates are exluded from tranmission rate change tables ("new waves", "slowing waves").
- Transmission rate, and its STD are calculated from growth rate and its STD using active cases estimation.
- For projections (into future) very noisy projections (with broad confidence bounds) are not shown in the tables.
- Where the rate estimated from Total Outstanding Cases is too high (on down-slopes) recovery probability if 1/20 is used (equivalent 20 days to recover).
- Total cases are estimated from the reported deaths for each country:
- Each country has a different testing policy and capacity and cases are under-reported in some countries. Using an estimated IFR (fatality rate) we can estimate the number of cases some time ago by using the total deaths until today.
- IFRs for each country is estimated using the age adjusted IFRs from May 1 New York paper and UN demographic data for 2020. These IFRs can be found in
df['age_adjusted_ifr']column. Some examples: US - 0.98%, UK - 1.1%, Qatar - 0.25%, Italy - 1.4%, Japan - 1.6%. - The average fatality lag is assumed to be 8 days on average for a case to go from being confirmed positive (after incubation + testing lag) to death. This is the same figure used by "Estimating The Infected Population From Deaths".
- Testing bias adjustment: the actual lagged fatality rate is than divided by the IFR to estimate the testing bias in a country. The estimated testing bias then multiplies the reported case numbers to estimate the true case numbers (=case numbers if testing coverage was as comprehensive as in the heavily tested countries).
- ICU need is calculated and age-adjusted as follows:
- UK ICU ratio was reported as 4.4% of active reported cases.
- Using UKs ICU ratio, UK's testing bias, and IFRs corrected for age demographics we can estimate each country's ICU ratio (the number of cases requiring ICU hospitalisation).